Adoption of dispersed renewable energy technologies requires transmission network expansion. Besides the transmission system operator (TSO), restructuring of electricity industries has introduced a merchant investor (MI), who earns congestion rents from constructing new lines. We compare these two market designs via a stochastic bi-level programming model that has either the MI or the TSO making transmission investment decisions at the upper level and power producers determining generation investment and operation at the lower level while facing wind power variability. We find that social welfare is always higher under the TSO because the MI has incentive to boost congestion rents by restricting capacities of transmission lines. Such strategic behavior also limits investment in wind power by producers. However, regardless of the market design (MI or TSO), when producers behave a la Cournot, a higher proportion of energy is produced by wind. In effect, withholding of generation capacity by producers prompts more transmission investment since the TSO aims to increase welfare by subsidizing wind and the MI creates more flow to maximize profit.

Research on electric power systems has considered the impact of foreseeable plug-in electric vehicle (PEV) penetration on its regulation, planning, and operation. Indeed, detailed treatment of PEV charging is necessary for efficient allocation of resources. It is envisaged that a coordinator of charging schedules, i.e., a PEV aggregator, could exercise some form of load control according to electricity market prices and network charges. In this context, it is important to consider the effects of uncertainty of key input parameters to optimization algorithms for PEV charging schedules. However, the modeling of the PEV aggregator's exposure to profit volatility has received less attention in detail. Hence, this paper develops a methodology to maximize PEV aggregator profits taking decisions in day-ahead and balancing markets while considering risk aversion. Under uncertain market prices and fleet mobility, the proposed two-stage linear stochastic program finds optimal PEV charging schedules at the vehicle level. A case study highlights the effects of including the conditional value-at-risk (CVaR) term in the objective function and calculates two metrics referred to as the expected value of aggregation and flexibility.

Environmental concerns have motivated governments in the European Union and elsewhere to set ambitious targets for generation from renewable energy (RE) technologies and to offer subsidies for their adoption along with priority grid access. However, because RE technologies like solar and wind power are intermittent, their penetration places greater strain on existing conventional power plants that need to ramp up more often. In turn, energy storage technologies, e.g., pumped hydro storage or compressed air storage, are proposed to offset the intermittency of RE technologies and to facilitate their integration into the grid. We assess the economic and environmental consequences of storage via a complementarity model of a stylized Western European power system with market power, representation of the transmission grid, and uncertainty in RE output. Although storage helps to reduce congestion and ramping costs, it may actually increase greenhouse gas emissions from conventional power plants in a perfectly competitive setting. Conversely, strategic use of storage by producers renders it less effective at curbing both congestion and ramping costs, while having no net overall impact on emissions.

The trend toward increasing energy efficiency and variable renewable energy (VRE) production has implications for combined heat and power (CHP) plants, which operate in both the price-driven power market and the district heating (DH) sector. Since CHP will be important in VRE integration, we develop a complementarity model to analyze CHP producers' roles in integrated markets. We use a Nordic case study to gain insights into (i) the effect of the link between CHP and DH on market power and (ii) market power's impact on operations in the DH sector. The results indicate that (i) the link of CHP to DH supply can increase market power and (ii) market power can induce shifts in DH production from heat-only to CHP.